Staff Software Engineer, AI/ML, Google Cloud

Google•Sunnyvale, CA

1d•$207,000 - $300,000

About The Position

Google software engineers develop technologies that help billions of users connect, explore, and interact with information. Engineers work on projects critical to Google's needs and may switch teams and projects as the business evolves. The role calls for versatility, leadership, and a willingness to take on problems across the full stack. The AI and Infrastructure team delivers AI and infrastructure capabilities to Google customers at scale, with a focus on efficiency, reliability, and velocity. Its customers include Googlers, Google Cloud customers, and Google users worldwide. The team supports AI model development, computing for global services, and platforms for developers, with work spanning software and hardware, including TPUs, Vertex AI for Google Cloud, Google Global Networking, data center operations, and systems research. Individual pay is determined by job-related skills, experience, and relevant education or training. The listed US compensation is $207,000–$300,000, plus a 20% bonus target, equity, and benefits.

Requirements

Bachelor’s degree or equivalent practical experience.
8 years of experience in software development.
5 years of experience in one or more of the following: speech/audio, reinforcement learning, ML infrastructure, or another specialized ML field.
5 years of experience leading ML design and optimizing end-to-end machine learning, including areas such as model deployment, model evaluation, data processing, debugging, and fine-tuning.
5 years of experience testing and launching software products.
3 years of experience with software design and architecture.

Nice To Haves

Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
8 years of experience with data structures and algorithms.
3 years of experience in a technical leadership role leading project teams and setting technical direction.
3 years of experience working in an organization involving cross-functional or cross-business projects.

Responsibilities

Design, develop, test, deploy, maintain, and enhance large-scale software solutions.
Provide technical leadership on high-impact projects and manage project priorities, deadlines, and deliverables.
Facilitate alignment and clarity across teams on goals, outcomes, and timelines.
Influence and coach a distributed team of engineers.
Lead the design and implementation of solutions in specialized ML areas, optimize ML infrastructure, and guide the development of model optimization and data processing strategies.